TypeError Traceback (most recent call last)
~/anaconda3/envs/fastai2/lib/python3.7/site-packages/numpy/lib/shape_base.py in array_split(ary, indices_or_sections, axis)
769 # handle array case.
–> 770 Nsections = len(indices_or_sections) + 1
771 div_points = [0] + list(indices_or_sections) + [Ntotal]
TypeError: object of type ‘int’ has no len()
During handling of the above exception, another exception occurred:
ValueError Traceback (most recent call last)
in
3 splitter=RandomSplitter())
4
----> 5 dbunch_lm = imdb_lm.dataloaders(df)
~/anaconda3/envs/fastai2/lib/python3.7/site-packages/fastai2/data/block.py in dataloaders(self, source, path, verbose, **kwargs)
105
106 def dataloaders(self, source, path=’.’, verbose=False, **kwargs):
–> 107 dsets = self.datasets(source)
108 kwargs = {**self.dls_kwargs, **kwargs, ‘verbose’: verbose}
109 return dsets.dataloaders(path=path, after_item=self.item_tfms, after_batch=self.batch_tfms, **kwargs)
~/anaconda3/envs/fastai2/lib/python3.7/site-packages/fastai2/data/block.py in datasets(self, source, verbose)
102 splits = (self.splitter or RandomSplitter())(items)
103 pv(f"{len(splits)} datasets of sizes {’,’.join([str(len(s)) for s in splits])}", verbose)
–> 104 return Datasets(items, tfms=self._combine_type_tfms(), splits=splits, dl_type=self.dl_type, n_inp=self.n_inp, verbose=verbose)
105
106 def dataloaders(self, source, path=’.’, verbose=False, **kwargs):
~/anaconda3/envs/fastai2/lib/python3.7/site-packages/fastai2/data/core.py in init(self, items, tfms, tls, n_inp, dl_type, **kwargs)
278 def init(self, items=None, tfms=None, tls=None, n_inp=None, dl_type=None, **kwargs):
279 super().init(dl_type=dl_type)
–> 280 self.tls = L(tls if tls else [TfmdLists(items, t, **kwargs) for t in L(ifnone(tfms,[None]))])
281 self.n_inp = ifnone(n_inp, max(1, len(self.tls)-1))
282
~/anaconda3/envs/fastai2/lib/python3.7/site-packages/fastai2/data/core.py in (.0)
278 def init(self, items=None, tfms=None, tls=None, n_inp=None, dl_type=None, **kwargs):
279 super().init(dl_type=dl_type)
–> 280 self.tls = L(tls if tls else [TfmdLists(items, t, **kwargs) for t in L(ifnone(tfms,[None]))])
281 self.n_inp = ifnone(n_inp, max(1, len(self.tls)-1))
282
~/anaconda3/envs/fastai2/lib/python3.7/site-packages/fastcore/foundation.py in call(cls, x, args, **kwargs)
39 return x
40
—> 41 res = super().call(((x,) + args), **kwargs)
42 res._newchk = 0
43 return res
~/anaconda3/envs/fastai2/lib/python3.7/site-packages/fastai2/data/core.py in init(self, items, tfms, use_list, do_setup, split_idx, train_setup, splits, types, verbose)
216 if do_setup:
217 pv(f"Setting up {self.tfms}", verbose)
–> 218 self.setup(train_setup=train_setup)
219
220 def _new(self, items, split_idx=None, **kwargs):
~/anaconda3/envs/fastai2/lib/python3.7/site-packages/fastai2/data/core.py in setup(self, train_setup)
232
233 def setup(self, train_setup=True):
–> 234 self.tfms.setup(self, train_setup)
235 if len(self) != 0:
236 x = super().getitem(0) if self.splits is None else super().getitem(self.splits[0])[0]
~/anaconda3/envs/fastai2/lib/python3.7/site-packages/fastcore/transform.py in setup(self, items, train_setup)
177 tfms = self.fs[:]
178 self.fs.clear()
–> 179 for t in tfms: self.add(t,items, train_setup)
180
181 def add(self,t, items=None, train_setup=False):
~/anaconda3/envs/fastai2/lib/python3.7/site-packages/fastcore/transform.py in add(self, t, items, train_setup)
180
181 def add(self,t, items=None, train_setup=False):
–> 182 t.setup(items, train_setup)
183 self.fs.append(t)
184
~/anaconda3/envs/fastai2/lib/python3.7/site-packages/fastcore/transform.py in setup(self, items, train_setup)
76 def setup(self, items=None, train_setup=False):
77 train_setup = train_setup if self.train_setup is None else self.train_setup
—> 78 return self.setups(getattr(items, ‘train’, items) if train_setup else items)
79
80 def _call(self, fn, x, split_idx=None, **kwargs):
~/anaconda3/envs/fastai2/lib/python3.7/site-packages/fastcore/dispatch.py in call(self, *args, **kwargs)
96 if not f: return args[0]
97 if self.inst is not None: f = MethodType(f, self.inst)
—> 98 return f(*args, **kwargs)
99
100 def get(self, inst, owner):
~/anaconda3/envs/fastai2/lib/python3.7/site-packages/fastai2/text/core.py in setups(self, dsets)
285 def setups(self, dsets):
286 if not self.mode == ‘df’ or not isinstance(dsets.items, pd.DataFrame): return
–> 287 dsets.items,count = tokenize_df(dsets.items, self.text_cols, rules=self.rules, **self.kwargs)
288 if self.counter is None: self.counter = count
289 return dsets
~/anaconda3/envs/fastai2/lib/python3.7/site-packages/fastai2/text/core.py in tokenize_df(df, text_cols, n_workers, rules, mark_fields, tok_func, res_col_name, **tok_kwargs)
215 rules = L(ifnone(rules, defaults.text_proc_rules.copy()))
216 texts = _join_texts(df[text_cols], mark_fields=mark_fields)
–> 217 outputs = L(parallel_tokenize(texts, tok_func, rules, n_workers=n_workers, **tok_kwargs)
218 ).sorted().itemgot(1)
219
~/anaconda3/envs/fastai2/lib/python3.7/site-packages/fastcore/foundation.py in call(cls, x, args, **kwargs)
39 return x
40
—> 41 res = super().call(((x,) + args), **kwargs)
42 res._newchk = 0
43 return res
~/anaconda3/envs/fastai2/lib/python3.7/site-packages/fastcore/foundation.py in init(self, items, use_list, match, *rest)
312 if items is None: items = []
313 if (use_list is not None) or not _is_array(items):
–> 314 items = list(items) if use_list else _listify(items)
315 if match is not None:
316 if is_coll(match): match = len(match)
~/anaconda3/envs/fastai2/lib/python3.7/site-packages/fastcore/foundation.py in _listify(o)
248 if isinstance(o, list): return o
249 if isinstance(o, str) or _is_array(o): return [o]
–> 250 if is_iter(o): return list(o)
251 return [o]
252
~/anaconda3/envs/fastai2/lib/python3.7/site-packages/fastai2/torch_core.py in parallel_gen(cls, items, n_workers, as_gen, **kwargs)
719 def parallel_gen(cls, items, n_workers=defaults.cpus, as_gen=False, **kwargs):
720 “Instantiate cls
in n_workers
procs & call each on a subset of items
in parallel.”
–> 721 batches = np.array_split(items, n_workers)
722 idx = np.cumsum(0 + L(batches).map(len))
723 queue = Queue()
<array_function internals> in array_split(*args, **kwargs)
~/anaconda3/envs/fastai2/lib/python3.7/site-packages/numpy/lib/shape_base.py in array_split(ary, indices_or_sections, axis)
774 Nsections = int(indices_or_sections)
775 if Nsections <= 0:
–> 776 raise ValueError(‘number sections must be larger than 0.’)
777 Neach_section, extras = divmod(Ntotal, Nsections)
778 section_sizes = ([0] +
ValueError: number sections must be larger than 0.